Manager, Applied AI Engineering (Enterprise)

About the job

Responsibilities

• Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers.
• Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion.
• Coach the team through decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost.
• Establish an operating model for prioritizing accounts and engagements according to customer needs, strategic value, technical complexity, and potential for repeatable impact.
• Serve as a senior technical escalation point during critical launches, production incidents, complex integrations, and high-stakes customer decisions.
• Partner with customer executives and technical leaders to connect implementation decisions to measurable business and operational outcomes.
• Help customers progress from experimentation to production systems and sustained adoption across their organizations.
• Partner closely with Sales and Solutions Engineering to create continuity throughout the customer lifecycle and maintain shared accountability for customer success.
• Translate customer needs and recurring implementation challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams.
• Identify scalable market patterns, distinguish them from bespoke requests, and advocate for investments that can benefit multiple customers.
• Develop reusable architectures, evaluation methods, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio.
• Establish mechanisms for measuring production implementations, adoption, customer outcomes, delivery quality, team capacity, and the impact of reusable work.
• Hire thoughtfully, raise the technical and leadership bar, and foster a culture of accountability, curiosity, collaboration, inclusion, and continuous learning.
• Represent OpenAI with credibility and sound judgment in conversations with senior customer and internal stakeholders.

Requirements

• Significant experience managing customer-facing technical teams, such as Applied AI Engineers, Solutions Architects, Forward Deployed Engineers, Customer Engineers, or Technical Account Managers.
• Experience building or leading teams responsible for implementing complex software, data, machine learning, or AI systems in enterprise environments.
• Sufficient technical depth to evaluate architectures, ask incisive questions, challenge assumptions, and coach engineers through difficult implementation decisions.
• Experience taking AI, machine learning, or other technically complex systems from prototype to production.
• Understanding of production-system requirements, including reliability, observability, security, privacy, data governance, evaluation, and operational readiness.
• Experience leading teams through ambiguity, competing priorities, escalations, and rapidly evolving products or markets.
• Ability to translate effectively among technical details, customer needs, product strategy, and business outcomes.
• Experience working with large organizations involving multiple business units, stakeholder groups, procurement processes, or governance requirements.
• Strong executive presence and ability to build trust with engineering leaders, business executives, security teams, and other senior stakeholders.
• Experience designing operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes for a growing technical organization.
• Strong cross-functional partnership skills, able to navigate disagreement directly while maintaining trust and shared accountability.
• Ability to use data and clear principles to allocate limited resources across a large portfolio of opportunities.
• Deep care for developing people, with a track record of coaching team members, raising performance, and building inclusive teams.
• Energized by helping organizations adopt frontier AI responsibly and turn emerging capabilities into durable value.